COVID‐19 as a Blood Clotting Disorder Masquerading as a Respiratory Illness: A Cerebrovascular Perspective and Therapeutic Implications for Stroke Thrombectomy
Why this work is in the frame
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Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as the name suggests was initially thought to only cause a respiratory illness. However, several reports have been published of patients with ischemic strokes in the setting of coronavirus disease 2019 (COVID-19). The mechanisms of how SARS-CoV-2 results in blood clots and large vessel strokes need to be defined as it has therapeutic implications. SARS-CoV-2 enters the blood stream by breaching the blood-air barrier via the lung capillary adjacent to the alveolus, and then attaches to the angiotensin-converting enzyme II receptors on the endothelial cells. Once SARS-CoV-2 enters the blood stream, a cascade of events (Steps 1-8) unfolds including accumulation of angiotensin II, reactive oxygen species, endothelial dysfunction, oxidation of beta 2 glycoprotein 1, formation of antiphospholipid antibody complexes promoting platelet aggregation, coagulation cascade, and formation of cross-linked fibrin blood clots, leading to pulmonary emboli (PE) and large vessel strokes seen on angiographic imaging studies. There is emerging evidence for COVID-19 being a blood clotting disorder and SARS-CoV-2 using the respiratory route to enter the blood stream. As the blood-air barrier is breached, varying degrees of collateral damage occur. Although antiviral and immune therapies are studied, the role of blood thinners in the prevention, and management of blood clots in Covid-19 need evaluation. In addition to ventilators and blood thinners, continuous aspiration and clot retrieval devices (approved in Europe, cleared in the United States) or cyclical aspiration devices (approved in Europe) need to be considered for the emergent management of life-threatening clots including PE and large vessel strokes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it